# Analysis Techniques: Flood Analysis Example with Instaneous Peak Flow Data (Log-Pearson Type III Distribution)

## Step 1: Obtain streamflow data

Obtain instantaneous peak streamflow data from the USGS web site.

• Go to http://oregon.usgs.gov
• Select Historical Water Data
• Select Surface Water
• Select Peaks
• Check box under Site Identifier for Site Name and Submit
• Type in Alsea under Site Name and select match any part and Submit
• Select gage at TIDEWATER (140306500)
• Select Tab-separated data
• For the example, copy entire data set into Excel worksheet
• Paste special as text (this will separate the data into columns)

## Step 3:  Rank the data from largest discharge to smallest discharge.

• Add a column for Rank and number each streamflow value from 1 to n (the total number of values in your dataset).

## Step 10:  Calculate the Sum for the {(logQ – avg(logQ))^2} and the {(logQ – avg(logQ))^3} columns.

Step 11:  Calculate the variance, standard deviation, and skew coefficient as follows:

variance =

standard deviation =

skew coefficient =

Excel functions can also be used to calculate the variance (=VAR( ) ), standard deviation (=STDEV( ) ), and skewness coefficient (=SKEW( ) ).  Note that you use these formulas with the data in the log(Q) column.

## Step 13:  Calculate k values

• Use the frequency factor table and the skew coefficient to find the k values for the 2,5,10,25,50,100, and 200 recurrence intervals
• If the skew coefficient is between two given skew coefficients in the table than you can linearly extrapolate between the two numbers to get the appropriate k value. To view the frequency factor table click on the "show me" link below.

## Step 14:  Using the general equation, list the discharges associated with each recurrence interval

general equation =

## Step 16:  Create Plot

Below is a comparison of flood frequency analysis completed using mean daily data versus instantaneous discharge data. As can be seen, had you completed this analysis using mean daily data, the result would have been an underestimation of the discharges associated with each return period.